How do I keep only specific rows based on whether a column has a specific value?

Question

I have a dataset which contains the order, species, and various trait data of species of birds. I am trying to make it so it only keeps data on certain orders. Normally when I am subsetting by species I merge datasets so that only those with the same row names, i.e. species names, are kept in the new data frame, but it appears that when using read.csv() row names cannot be duplicates, and as the Order names would be duplicates, I cannot have them as row names. So how would I subset it so that the new data frame only contains information on select Orders? This is how the columns with Orders and Species look like:

                                        Order1                      Species
Acanthagenys_rufogularis         Passeriformes     Acanthagenys_rufogularis
Acanthiza_apicalis               Passeriformes           Acanthiza_apicalis
Acanthiza_chrysorrhoa            Passeriformes        Acanthiza_chrysorrhoa
Acanthiza_lineata                Passeriformes            Acanthiza_lineata
Acanthiza_nana                   Passeriformes               Acanthiza_nana
Acanthiza_pusilla                Passeriformes            Acanthiza_pusilla
Acanthiza_reguloides             Passeriformes         Acanthiza_reguloides
Acanthiza_uropygialis            Passeriformes        Acanthiza_uropygialis
Acanthorhynchus_tenuirostris     Passeriformes Acanthorhynchus_tenuirostris
Accipiter_cirrocephalus        Accipitriformes      Accipiter_cirrocephalus

While the first 10 lines only contain 2 orders, the dataset contains information on 26 Avian Orders, and I am only interested in Passeriformes, Charadriiformes, Psittaciformes, & Struthioniformes

Answer 1

Assuming your data frame is called bird_df after you've read it in with read.csv(), you can subset the data to only contain rows where Order1 is equal to Passeriformes, Charadriiformes, Psittaciformes, or Struthioniformes using:

subset_bird_df <- bird_df[bird_df$Order1 %in% c("Passeriformes", "Charadriiformes", "Psittaciformes", "Struthioniformes"),]